A hierarchical algorithm for fuzzy template matching in emotional facial images
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Computational intelligence models for image processing and information reasoning
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Template matching is a technique for finding the location of a reference image or an object inside a scene image. The conventional method of template matching uses cross correlation algorithms. The method is simple to implement and understand, but it is one of the slowest methods. Furthermore, if the object in the image is rotated, the tradition method can fail. In this paper, an algorithm for a rotation invariant template matching method is proposed. The algorithm consists of two stages process. In the first stage, the scene image and template one are reduced in resolution. Then the features of the subimage covered by the template are extracted using RPT (Ring Projection Transformation) method. The normalized correlation formula is used to select the matching candidates in the coarse search stage. These candidates will be recovered to original position and determine the searching range. In the second stage process, Zernike moments based on the matching candidates are used to determine the optimal matching point.